In this paper we propose a computer vision-based technique that mines existing spatial image databases for discovery of zebra crosswalks in urban settings. Knowing the location of crosswalks is critical for a blind person planning a trip that includes street crossing. By augmenting existing spatial databases (such as Google Maps or OpenStreetMap) with this information, a blind traveler may make more informed routing decisions, resulting in greater safety during independent travel. Our algorithm first searches for zebra crosswalks in satellite images; all candidates thus found are validated against spatially registered Google Street View images. This cascaded approach enables fast and reliable discovery and localization of zebra crosswalks in large image datasets. While fully automatic, our algorithm could also be complemented by a final crowdsourcing validation stage for increased accuracy.
Zebra crossing spotter: automatic population of spatial databases for increased safety of blind travelers / D. Ahmetovic, J.M. Coughlan, R. Manduchi, S. Mascetti - In: ASSETS 2015 : proceedingsNew York : ACM, 2015. - ISBN 9781450334006. - pp. 251-258 (( Intervento presentato al 17. convegno Conference on Computers and Accessibility tenutosi a Lisbon nel 2015 [10.1145/2700648.2809847].
Zebra crossing spotter: automatic population of spatial databases for increased safety of blind travelers
D. AhmetovicPrimo
;S. MascettiUltimo
2015
Abstract
In this paper we propose a computer vision-based technique that mines existing spatial image databases for discovery of zebra crosswalks in urban settings. Knowing the location of crosswalks is critical for a blind person planning a trip that includes street crossing. By augmenting existing spatial databases (such as Google Maps or OpenStreetMap) with this information, a blind traveler may make more informed routing decisions, resulting in greater safety during independent travel. Our algorithm first searches for zebra crosswalks in satellite images; all candidates thus found are validated against spatially registered Google Street View images. This cascaded approach enables fast and reliable discovery and localization of zebra crosswalks in large image datasets. While fully automatic, our algorithm could also be complemented by a final crowdsourcing validation stage for increased accuracy.File | Dimensione | Formato | |
---|---|---|---|
CameraReady.pdf
accesso riservato
Tipologia:
Post-print, accepted manuscript ecc. (versione accettata dall'editore)
Dimensione
1.96 MB
Formato
Adobe PDF
|
1.96 MB | Adobe PDF | Visualizza/Apri Richiedi una copia |
Pubblicazioni consigliate
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.